New Haven, KY
New Haven, KY's wildfire risk, in USFS's own numbers
Out of every US place USFS scores, New Haven lands at the 24th percentile for wildfire risk to structures — close to the middle of USFS's national wildfire-risk range — a figure built from its 503 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts New Haven at the 26th percentile, close to its 24th-percentile risk score.
What "at risk" means for the buildings here
Direct exposure dominates in New Haven: 55.9% of its 503 buildings, versus 44.1% Indirect and 0% Minimal. Clearing space around a structure changes the outcome here more than any single building-material swap.
How New Haven compares
New Haven's 44th-percentile standing inside Kentucky outpaces its 24th national percentile — this is a hotter spot than most of its own state, even though the state as a whole runs cooler nationally. Among the 31,521 US communities USFS scores, New Haven ranks 24,014 for wildfire risk (1 is highest) and 17,285 by building count (1 is largest). Within Kentucky alone, it ranks 307 of 552 places by risk. See the full county-by-county picture for Kentucky on its state page.
New Haven and the insurance market
New Haven's moderate wildfire rating (24th percentile) isn't the kind of score driving the carrier pullback making news in the highest-risk Western markets — but a standard homeowners quote is still worth comparing on its own terms.
What would actually reduce this score
Because Direct exposure dominates in New Haven (55.9%), the highest-leverage fix is defensible space, not roofing or vents alone — covered in the home-hardening guide.
Where New Haven's figures come from
Every one of the two percentiles behind New Haven's 24,014-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what New Haven's dominant direct exposure actually means, with real examples from across the dataset.